Background motion vector detection

ABSTRACT

A selector ( 502 ) for selecting a background motion vector for a pixel in an occlusion region of an image, from a set of motion vectors being computed for the image, comprises: computing means ( 510 ) for computing a model-based motion vector for the pixel on basis of a motion model being determined on basis of a part of ( 402 - 436 ) a motion vector field ( 400 ) of the image; comparing means ( 511 ) for comparing the model-based motion vector with each of the motion vectors of the set of motion vectors; and selecting means ( 512 ) for selecting a particular motion vector of the set of motion vectors on basis of the comparing and for assigning the particular motion vector as the background motion vector.

The invention relates to a selector for selecting a background motionvector for a pixel in an occlusion region of an image, from a set ofmotion vectors being computed for the image.

The invention further relates to an up-conversion unit for computing apixel value in an occlusion region of an output image, on basis of asequence of input images, the up-conversion unit comprising:

a motion estimation unit for estimating motion vectors of the image, themotion vectors forming a motion vector field;

a detection unit for detecting the occlusion region in the image, onbasis of the motion vectors;

a motion model determination unit for determining a motion model onbasis of a part of the motion vector field;

an interpolating unit for computing the pixel value by means of temporalinterpolation, on basis of a background motion vector; and

the selector for selecting the background motion vector for the pixel,as described above.

The invention further relates to an image processing apparatuscomprising:

receiving means for receiving a signal corresponding to a sequence ofinput images; and

an up-conversion unit as described above.

The invention further relates to a method of selecting a backgroundmotion vector for a pixel in an occlusion region of an image, from a setof motion vectors being computed for the image.

The invention further relates a computer program product to be loaded bya computer arrangement, comprising instructions to select a backgroundmotion vector for a pixel in an occlusion region of an image, from a setof motion vectors being computed for the image.

In images resulting from motion compensated image rate converters,artifacts are visible at the boundaries of moving objects, where eithercovering or uncovering of background occurs. These artifacts are usuallyreferred to as halos. There are two reasons for these halos. The first,rather trivial, cause is the resolution of the motion vector field.Usually, the density of the grid at which the motion vectors areavailable is much less than that of the pixel grid. If, for example,motion vectors are available for blocks of 8×8 pixels then the contoursof moving objects can only roughly be approximated at the vector grid,resulting in a blocky halo effect. A second, less trivial cause, is thata motion estimation unit, estimating motion between two successiveimages of a video sequence, cannot perform well in regions wherecovering or uncovering occurs, as it is typical for these regions thatthe background information only occurs in either of the two images.

Moreover, up-conversion units usually combine information from bothimages, i.e. bi-directional interpolation, using the wrongly estimatedmotion vectors, to create the up-converted image. Since, one of theseimages does not contain the correct information, due to the occlusion,the up-converted image is incorrect for occlusion regions.

In order to solve these problems, an up-conversion unit should be ableto detect the occlusion regions, detect the type of occlusion present inthese regions (i.e. covering or uncovering), determine the correctmotion vectors for these regions, and perform the up-conversion. Thebook “Video processing for multimedia systems”, by G. de Haan,University Press Eindhoven, 2000, ISBN 90-9014015-8, chapter 4,describes methods for the detection of occlusion regions and for thecovering/uncovering classification. So, remains the requirement fordetermining the correct motion vector in occlusion regions.

It is an object of the invention to provide a selector for easilydetermining an appropriate motion vector in an occlusion region.

This object of the invention is achieved in that the selector comprises:

computing means for computing a model-based motion vector for the pixelon basis of a motion model being determined on basis of a part of amotion vector field of the image;

comparing means for comparing the model-based motion vector with each ofthe motion vectors of the set of motion vectors; and

selecting means for selecting a particular motion vector of the set ofmotion vectors on basis of the comparing and for assigning theparticular motion vector as the background motion vector.

Typically, the set of motion vectors being computed for the occlusionregion comprises a motion vector which corresponds with the movement ofthe foreground, i.e. the foreground motion vector and a motion vectorwhich corresponds with the movement of the background, i.e. thebackground motion vector. However it is not directly known which one ofthe motion vectors of the set corresponds to the background. Thisbackground motion vector might correspond to the null vector, i.e. nomotion. However, it is to be noticed that in many cases the camera ismoving to track the main subject of the scene. That means that theforeground motion vector corresponds to the null vector and thebackground motion vector is not equal to the null vector.

To select the background motion vector from the set of motion vectors,use is made of a global motion model of the background of the image.Based on the model a model-based motion vector is determined for theparticular pixel. The motion vectors of the set are compared with themodel-based motion vector. The one which fits best is selected as thebackground motion vector.

Preferably the global motion model is based on motion vectors of theborders of the motion vector field. In other words, the part of themotion vector field which is applied for determining the motion modelcorresponds with motion vectors being estimated for groups of pixels inthe neighborhood of the borders of the image. The probability that thesemotion vectors correspond with the background is relatively high.

In an embodiment of the selector according to the invention, thecomparing unit is arranged to compute differences between themodel-based motion vector and the respective motion vectors of the setof motion vectors and the selecting unit is arranged to select theparticular motion vector if the corresponding difference is the minimumdifference of the differences. The difference might be a L₁-norm, i.e.the sum of absolute differences of the components of the motion vectorsto be compared. Alternatively, the difference is a L₂-norm, i.e. the sumof squared differences of the components of the motion vectors to becompared.

In an embodiment of the selector according to the invention, the motionmodel comprises translation and zoom. The parameters of such a model arerelatively easy to compute, while the model is robust. With such apan-zoom model the most frequent geometrical operations within videoimages can be described. With this pan-zoom model, the model-basedmotion vector {right arrow over (D)}_(b) for a particular pixel can bedetermined by: $\begin{matrix}{{\overset{\rightarrow}{D}}_{b} = \begin{bmatrix}{t_{x} + {z_{x}x}} \\{t_{y} + {z_{y}y}}\end{bmatrix}} & (1)\end{matrix}$where t_(x) and t_(y) define the translation, z_(x) and z_(y) define thezoom and x and y the location in the image. In U.S. Pat. No. 6,278,736and in the article “An efficient true-motion estimator using candidatevectors from a parametric motion model”, by G. de Haan, et al., in IEEETransactions on circuits and systems for video technology, Vol. 8, no.1, pages 85-91, March 1998 is described how a motion model can be madebased on a part of a motion vector field.

It is a further object of the invention to provide an up-conversion unitof the kind described in the opening paragraph comprising a selector foreasily determining an appropriate motion vector in an occlusion region.

This object of the invention is achieved in that the selector forselecting the background motion vector for the pixel is as claimed inclaim 1.

It is a further object of the invention to provide an image processingapparatus of the kind described in the opening paragraph comprising aselector for easily determining an appropriate motion vector in anocclusion region.

This object of the invention is achieved in that the selector forselecting the background motion vector for the pixel is as claimed inclaim 1.

The image processing apparatus may comprise additional components, e.g.a display device for displaying the output images. The image processingapparatus might support one or more of the following types of imageprocessing:

Video compression, i.e. encoding or decoding, e.g. according to the MPEGstandard.

De-interlacing: Interlacing is the common video broadcast procedure fortransmitting the odd or even numbered image lines alternately.De-interlacing attempts to restore the full vertical resolution, i.e.make odd and even lines available simultaneously for each image;

Inage rate conversion: From a series of original input images a largerseries of output images is calculated. Output images are temporallylocated between two original input images; and

Temporal noise reduction. This can also involve spatial processing,resulting in spatial-temporal noise reduction.

The image processing apparatus might e.g. be a TV, a set top box, a VCR(Video Cassette Recorder) player, a satellite tuner, a DVD (DigitalVersatile Disk) player or recorder.

It is a further object of the invention to provide a method for easilydetermining an appropriate motion vector in an occlusion region.

This object of the invention is achieved in that the method comprises:

computing a model-based motion vector for the pixel on basis of a motionmodel being determined on basis of a part of a motion vector field ofthe image;

comparing the model-based motion vector with each of the motion vectorsof the set of motion vectors;

selecting a particular motion vector of the set of motion vectors onbasis of the comparing and for assigning the particular motion vector asthe background motion vector.

It is a further object of the invention to provide a computer programproduct of the kind described in the opening paragraph for easilydetermining an appropriate motion vector in an occlusion region.

This object of the invention is achieved in that the computer programproduct, after being loaded, provides processing means with thecapability to carry out:

computing a model-based motion vector for the pixel on basis of a motionmodel being determined on basis of a part of a motion vector field ofthe image;

comparing the model-based motion vector with each of the motion vectorsof the set of motion vectors;

selecting a particular motion vector of the set of motion vectors onbasis of the comparing and for assigning the particular motion vector asthe background motion vector.

Modifications of the selector and variations thereof may correspond tomodifications and variations thereof of the method, the up-conversionunit, the image processing apparatus and the computer program productdescribed.

These and other aspects of the selector, of the method, theup-conversion unit, the image processing apparatus and of the computerprogram product according to the invention will become apparent from andwill be elucidated with respect to the implementations and embodimentsdescribed hereinafter and with reference to the accompanying drawings,wherein:

FIG. 1 schematically shows an image sequence containing a moving ball;

FIG. 2 schematically shows a 2-D representation of the situationdepicted in FIG. 1;

FIG. 3A and FIG. 3B schematically show bi-directional matches used inprior art motion estimation;

FIG. 4 schematically shows which part of a motion vector field is usedto determine a motion model according to the invention;

FIG. 5 schematically shows an up-conversion unit according to theinvention; and

FIG. 6 schematically shows an embodiment of the image processingapparatus according to the invention.

Same reference numerals are used to denote similar parts throughout thefigures.

Consider the situation in FIG. 1. Two successive original, i.e. input,images 100 and 104 are given at a first point in time n−1 and a secondpoint in time n, respectively. These images 100 and 104 schematicallyshow a ball 106 moving from left to right. An intermediate image 102 iscreated at n−a with 0<a<1. This intermediate image 102 is constructedfrom both original images 100 and 104. The quantity time correspondswith the axis 108. The vertical co-ordinates correspond with the axis110 and the horizontal co-ordinates correspond with the axis 112. It isassumed that the ball has a velocity of {right arrow over (f)}g and thatthe background is stationary, i.e. {right arrow over (b)}g={right arrowover (0)}.

FIG. 2 schematically shows a 2-D representation of the situationdepicted in FIG. 1. Note that FIG. 2 is rotated with respect to FIG. 1.Only the temporal 108 and the horizontal 112 axes are shown. The ball106 is now represented by the Grey rectangle. The motion trajectories ofthe ball 106 and of the background are indicated by the arrows 114 and116, respectively. The output image 102 image at n−a is created bymotion compensated interpolation, using motion vectors estimated to bevalid at n−a. The problems in the motion estimation unit andinterpolator according to the prior art, causing the halo, will bediscussed below.

In general, a motion estimation unit determines a motion vector for agroup of pixels by selecting the best matching motion vector from a setof candidate motion vectors. The match error is usually a Sum ofAbsolute Differences (SAD) obtained by fetching pixels from the inputimage at n−1 and comparing those pixels with pixels fetched from theinput image at n, using the candidate motion vector, i.e.:$\begin{matrix}{{ɛ\left( {\overset{\rightarrow}{D},\overset{\rightarrow}{X},n} \right)} = {\sum\limits_{\overset{\rightarrow}{x} \in \quad{B{(\overset{\rightarrow}{X})}}}\quad{{{F\left( {{\overset{\rightarrow}{x} - {\left( {1 - \alpha} \right)\overset{\rightarrow}{D}}},{n - 1}} \right)} - {F\left( {{\overset{\rightarrow}{x} + {\alpha\quad\overset{\rightarrow}{D}}},n} \right)}}}}} & (2)\end{matrix}$here {right arrow over (D)} is the motion vector, B({right arrow over(X)}) is the block located at block position {right arrow over (X)},{right arrow over (x)} is a pixel position, F({right arrow over (x)},n)is a luminance frame, n is the image number and a is a relativeposition. An example is given in FIG. 3A. The motion vector {right arrowover (D)}₁ points to the same information in both images, hence it has alow match error. The motion vector {right arrow over (D)}₂ points toinformation in image 100 at time n−1 which differs from the informationin image 104 at time n. A high match error is the result.

A problem occurs in occlusion areas. In these areas no motion vector canresult in a correct match since the information is not present in one ofthe two frames. In case of uncovering new information appears and istherefore not present in image 100 at time n−1. In case of coveringinformation disappears and is therefore not present in image 104 at timen. The result of this is that the motion vector field is erroneous inocclusion areas. FIG. 3B shows these problem areas 118 and 120 in Grey.The black dots 122 and 124 represent pixels for which a motion vectorhas to be estimated. The black dots 122 and 124 are located in thebackground, but since the background is covered in either image 100 attime n−1 or image 104 at time n there is no motion vector whichdescribes the motion of these image parts.

In known up-conversion units, usually pixel value information from bothimages, F(n) and F(n−1), is used for interpolation. For example, motioncompensated averaging uses a motion compensated pixel from the image 100at time n−1 and a motion compensated pixel from the image 104 at time n:$\begin{matrix}{{F\left( {\overset{\rightarrow}{x},{n - \alpha}} \right)} = \frac{{F\left( {{\overset{\rightarrow}{x} - {\left( {1 - \alpha} \right)\overset{\rightarrow}{D}}},{n - 1}} \right)} + {F\left( {{\overset{\rightarrow}{x} + {\alpha\quad\overset{\rightarrow}{D}}},n} \right)}}{2}} & (3)\end{matrix}$Even if the correct motion vector is used, the result in occlusion areasis erroneous since either the pixel from the image 100 at time n−1 orfrom the image 104 at time n is wrong.

A solution to the halo problem comprises at least two actions. Firstly,adjust the probably wrong motion vector in occlusion regions such thatthe correct motion vector is used in the up-conversion. Secondly, usingthe correct motion vector, fetch the pixel value information from thecorrect image, i.e. use unidirectional fetches instead of bi-directionalfetches.

There are some difficulties however. In order to perform the firstaction it must be known where the occlusion areas are. Hence occlusiondetection and foreground/background motion detection is required.

In order to perform the second action it must be known what type ofocclusion there is. If it is covering, then the pixel value informationfrom the image at time n−1 must be fetched. If it is uncovering, thenthe pixel value information from the image at time n must be fetched.Hence covering/uncovering detection is required. The book “Videoprocessing for multimedia systems”, by G. de Haan, University PressEindhoven, 2000, ISBN 90-9014015-8, chapter 4, describes methods for thedetection of occlusion regions and for the covering/uncoveringclassification.

In the following the foreground/background motion detection according tothe invention is described. FIG. 4 schematically shows which part of amotion vector field 400 is used to determine a global motion model ofthe background, according to the invention. It is assumed that thebackground motion is present at the borders of the image. Hence, anumber of motion vectors belonging to blocks of pixels located at theborder of the image, i.e. at the border of motion vector field are usedto determine the motion model of the background of the image. The methodto determine a motion model is described in detail in patentspecification U.S. Pat. No. 6,278,736 and in the article “An efficienttrue-motion estimator using candidate vectors from a parametric motionmodel”, by G. de Haan, et al., in IEEE Transactions on circuits andsystems for video technology, Vol. 8, no. 1, pages 85-91, March 1998.This method determines a pan-zoom model from the motion vector of pairsof blocks and takes the component-wise median as the global pan-zoommodel. A difference between the approach according to the invention andthe one mentioned in the cited article is the choice of the blocks. Inthe approach according to the invention blocks from the borders of theimage are used. Preferably 5 blocks 402-410 from the top, 5 blocks412-420 from the bottom border, 4 blocks 422-428 from the left and 4blocks 430-436 from the right border are used. That means a total of 18blocks. With this pan-zoom model, the model-based motion vector {rightarrow over (D)}_(b) for a particular pixel can be determined by means ofEquation 1.

In order to determine the background motion vector of a location {rightarrow over (x)}, in an occlusion region a set of motion vectors beingdetermined by the motion estimation unit are required. Typically thisset of motion vector comprises two motion vectors. The first one is theone which has been estimated for the location {right arrow over (x)} bythe motion estimation unit 502: {right arrow over (D)}_(c)={right arrowover (D)}({right arrow over (x)}) and an alternative motion vector in amotion vector being determined for a location {right arrow over (x)}+δin the neighborhood, {right arrow over (D)}_(a)={right arrow over(D)}({right arrow over (x)}+δ). In general, one of these motion vectorscorresponds to the foreground motion vector and the other corresponds tothe background motion vector. In order to determine the alternativemotion vector {right arrow over (D)}_(a), motion vectors from locationsa number of pixels (typically δ=16) to the left {right arrow over(D)}_(l) and right {right arrow over (D)}_(r) of the current positionare evaluated. The motion vector being most different from the currentvector is selected as the alternative motion vector {right arrow over(D)}_(a), $\begin{matrix}{{{\overset{\rightarrow}{D}}_{l} = {\overset{\rightarrow}{D}\left( {\overset{\rightarrow}{x} - \left( {16,0} \right)} \right)}}{{\overset{\rightarrow}{D}}_{r} = {\overset{\rightarrow}{D}\left( {\overset{\rightarrow}{x} + \left( {16,0} \right)} \right)}}} & (4) \\{\overset{\rightarrow}{D_{a}} = \left\{ \begin{matrix}{{\overset{\rightarrow}{D_{l}}\quad{if}\quad{{\overset{\rightarrow}{D_{l}} - \overset{\rightarrow}{D_{c}}}}} < {{\overset{\rightarrow}{D_{r}} - \overset{\rightarrow}{D_{c}}}}} \\{{\overset{\rightarrow}{D_{r}}\quad{if}\quad{{\overset{\rightarrow}{D_{l}} - \overset{\rightarrow}{D_{c}}}}} < {{\overset{\rightarrow}{D_{r}} - \overset{\rightarrow}{D_{c}}}}}\end{matrix} \right.} & (5)\end{matrix}$where {right arrow over (D)}({right arrow over (x)}) is the vectorfield. (See also U.S. Pat. No. 5,777,682)

In order to classify the motion vectors {right arrow over (D)}_(c) and{right arrow over (D)}_(a) into foreground and background these motionvectors are compared with the motion vector which is computed on basisof the motion model for the background of the image, {right arrow over(D)}_(b). The actual background vector is the motion vector which hasthe minimal distance to {right arrow over (D)}_(b), i.e.:If |{right arrow over (D)} _(c) −{right arrow over (D)} _(b) |<|{rightarrow over (D)} _(a) −{right arrow over (D)} _(b) |{right arrow over(b)}g={right arrow over (D)} _(c) and {right arrow over (f)}g={rightarrow over (D)}_(a)  (6)If |{right arrow over (D)} _(c) −{right arrow over (D)} _(b) |≧|{rightarrow over (D)} _(a) −{right arrow over (D)} _(b) |{right arrow over(b)}g={right arrow over (D)} _(a) and {right arrow over (f)}g={rightarrow over (d)}_(c)  (7)

FIG. 5 schematically shows an up-conversion unit 500 according to theinvention. The up-conversion unit is arranged to compute a pixel valuein an occlusion region of an output image, on basis of a sequence ofinput images. The up-conversion unit comprises:

a motion estimation unit 504 for estimating motion vectors of the image.The motion vectors form a motion vector field. The motion estimationunit is e.g. as specified in the article “True-Motion Estimation with3-D Recursive Search Block Matching” by G. de Haan et. al. in IEEETransactions on circuits and systems for video technology, vol. 3, no.5, October 1993, pages 368-379;

a detection unit 508 for detecting the occlusion regions in the image,on basis of the motion vectors. This detection unit 508 is specified inmore detail in the book “Video processing for multimedia systems”, by G.de Haan, University Press Eindhoven, 2000, ISBN 90-9014015-8, chapter 4;

a motion model determination unit 505 for determining a motion model onbasis of a part of the motion vector field. This motion modeldetermination unit 505 is as described in connection with FIG. 4;

an interpolating unit 506 for computing the pixel value of the outputimage 102 by means of temporal interpolation, on basis of a backgroundmotion vector; and

a selector 502 for selecting the background motion vector for the pixel,as described above. This selector comprises:

a motion vector computing unit 510 for computing a model-based motionvector {right arrow over (D)}_(b) for the pixel on basis of a motionmodel being determined on basis of a part 402-436 of a motion vectorfield 400 of the image;

a comparing unit 511 for comparing the model-based motion vector {rightarrow over (D)}_(b) with each of the motion vectors {right arrow over(D)}_(c) and {right arrow over (D)}_(a) of the set of motion vectors;

a selector unit 512 for selecting a particular motion vector of the setof motion vectors on basis of the comparing and for assigning theparticular motion vector as the background motion vector.

The motion estimation unit 504, the detection unit 508, the motion modeldetermination unit 505, the interpolating unit 506, and the selector 502may be implemented using one processor. Normally, these functions areperformed under control of a software program product. During execution,normally the software program product is loaded into a memory, like aRAM, and executed from there. The program may be loaded from abackground memory, like a ROM, hard disk, or magnetically and/or opticalstorage, or may be loaded via a network like Internet. Optionally anapplication specific integrated circuit provides the disclosedfunctionality.

The working of the up-conversion unit 500 is as follows. On the inputconnector 514 a signal representing a series of input images 100 and 104is provided. The up-conversion unit 500 is arranged to provide a seriesof output images at the output connector 516, comprising the inputimages 100 and 104 and intermediate images, e.g. 102. The motionestimation unit 504 is arranged to compute a motion vector field 400 forthe intermediate image on basis of the input images 100 and 104. Onbasis of the pixel values 524 of the input images 100 and 104 and onbasis of the motion vectors 522 the interpolating unit 506 is arrangedto compute the pixel values of the intermediate image 102. In principlethis is done by means of a bi-directional fetch of pixel values.However, as explained above, this results in artifacts in occlusionregions. Because of that, the up-conversion unit 500 according to theinvention is arranged to perform an alternative interpolation for theseocclusion regions.

The up-conversion unit 500 comprises a detection unit 508 for detectingthe occlusion regions in the image and for control of the interpolatingunit 506. The detection unit 508 is arranged to classify the type ofocclusion as described in patent application EP1048170. Theclassification is based on comparing neighboring motion vectors. Theclassification is as follows: $\begin{matrix}{{occlusion} = \left\{ \begin{matrix}{{{uncovering}\quad{if}\quad D_{l,x}} < D_{r,x}} \\{{{covering}\quad{if}\quad D_{l,x}} > D_{r,x}}\end{matrix} \right.} & (8)\end{matrix}$with D_(l,x) the x-component of the left motion vector and D_(r,x) thex-component of the right motion vector to be compared. The detectionunit 508 provides the selector 502 with a set of motion vectors 518.Typically this set of motion vectors comprises two motion vectors. Theselector 502 is arranged to determine which of these motion vectorscorresponds to the background motion and which of these motion vectorscorresponds with the foreground motion. On basis of the backgroundmotion vector 526 the interpolation unit 506 is arranged to fetch thecorresponding pixel value in the appropriate image:

in the case of covering the background motion vector is applied to fetchthe pixel value in image at time n−1; and

in the case of uncovering the background motion vector is applied tofetch the pixel value in image at time n;

Optionally additional pixel values are fetched in both preceding andsucceeding images on basis of an other motion vector. By means of afiltering operation, e.g. an order statistical operation like a median,the eventual pixel value of the intermediate image is computed.

In summary the halo reduction is as follows. The halo reduction startsby determining the occlusion regions. Only in the occlusion regions theupconversion deviates from the “normal” upconversion, motion compensatedaveraging, as specified in Equation 3. In occlusion regions the motionvector field is inaccurate. Therefore, it is tested whether or not analternative motion vector {right arrow over (D)}_(a) is better than theone {right arrow over (D)}_(c) which has been estimated by the motionestimation unit 504 for the current pixel. These two motion vectors, thecurrent {right arrow over (D)}_(c) and alternate {right arrow over(D)}_(a) motion vector are provided to the selector 502 which isarranged to determine the background motion vector. With the appropriatemotion vector the appropriate pixel value is fetched from the precedingor succeeding image.

FIG. 6 schematically shows an embodiment of the image processingapparatus 600 according to the invention, comprising:

Receiving means 602 for receiving a signal representing input images.The signal may be a broadcast signal received via an antenna or cablebut may also be a signal from a storage device like a VCR (VideoCassette Recorder) or Digital Versatile Disk (DVD). The signal isprovided at the input connector 608;

The up-conversion unit 500 as described in connection with FIG. 5; and

A display device 606 for displaying the output images of theup-conversion unit 500.

The image processing apparatus 600 might e.g. be a TV. Alternatively theimage processing apparatus 600 does not comprise the optional displaydevice 606 but provides the output images to an apparatus that doescomprise a display device 606. Then the image processing apparatus 600might be e.g. a set top box, a satellite-tuner, a VCR player, a DVDplayer or recorder. Optionally the image processing apparatus 600comprises storage means, like a hard-disk or means for storage onremovable media, e.g. optical disks. The image processing apparatus 600might also be a system being applied by a film-studio or broadcaster.

It should be noted that the above-mentioned embodiments illustraterather than limit the invention and that those skilled in the art willbe able to design alternative embodiments without departing from thescope of the appended claims. In the claims, any reference signs placedbetween parentheses shall not be constructed as limiting the claim. Theword ‘comprising’ does not exclude the presence of elements or steps notlisted in a claim. The word “a” or “an” preceding an element does notexclude the presence of a plurality of such elements. The invention canbe implemented by means of hardware comprising several distinct elementsand by means of a suitable programmed computer. In the unit claimsenumerating several means, several of these means can be embodied by oneand the same item of hardware.

1. A selector (502) for selecting a background motion vector for a pixelin an occlusion region of an image, from a set of motion vectors beingcomputed for the image, the selector (502) comprising: computing means(510) for computing a model-based motion vector for the pixel on basisof a motion model being determined on basis of a part of (402-436) amotion vector field (400) of the image; comparing means (511) forcomparing the model-based motion vector with each of the motion vectorsof the set of motion vectors; and selecting means (512) for selecting aparticular motion vector of the set of motion vectors on basis of thecomparing and for assigning the particular motion vector as thebackground motion vector.
 2. A selector (502) as claimed in claim 1,wherein the part of the motion vector field (400) corresponds withmotion vectors being estimated for groups of pixels in the neighborhoodof the borders of the image.
 3. A selector (502) as claimed in claim 1,wherein the comparing unit is arranged to compute differences betweenthe model-based motion vector and the respective motion vectors of theset of motion vectors and the selecting unit is arranged to select theparticular motion vector if the corresponding difference is the minimumdifference of the differences.
 4. A selector (502) as claimed in claim1, wherein the motion model comprises translation and zoom.
 5. Anup-conversion unit (500) for computing a pixel value in an occlusionregion of an output image, on basis of a sequence of input images, theup-conversion unit (500) comprising: a motion estimation unit (504) forestimating motion vectors of the image, the motion vectors forming amotion vector field (400); a detection unit (508) for detecting theocclusion region in the image, on basis of the motion vectors; a motionmodel determination unit (505) for determining a motion model on basisof a part of (402-436) the motion vector field (400); an interpolatingunit (506) for computing the pixel value by means of temporalinterpolation, on basis of a background motion vector; and the selector(502) for selecting the background motion vector for the pixel, asclaimed in claim
 1. 6. An image processing apparatus (600) comprising:receiving means (602) for receiving a signal corresponding to a sequenceof input images; and an up-conversion unit (500) for computing a pixelvalue in an occlusion region of an output image, as claimed in claim 5.7. An image processing apparatus (600) as claimed in claim 6,characterized in further comprising a display device (606) fordisplaying the output image.
 8. An image processing apparatus (600) asclaimed in claim 7, characterized in that it is a TV.
 9. A method ofselecting a background motion vector for a pixel in an occlusion regionof an image, from a set of motion vectors being computed for the image,the method comprising: computing a model-based motion vector for thepixel on basis of a motion model being determined on basis of a part of(402-436) a motion vector field (400) of the image; comparing themodel-based motion vector with each of the motion vectors of the set ofmotion vectors; and selecting a particular motion vector of the set ofmotion vectors on basis of the comparing and for assigning theparticular motion vector as the background motion vector.
 10. A computerprogram product to be loaded by a computer arrangement, comprisinginstructions to select a background motion vector for a pixel in anocclusion region of an image, from a set of motion vectors beingcomputed for the image, the computer arrangement comprising processingmeans and a memory, the computer program product, after being loaded,providing said processing means with the capability to carry out:computing a model-based motion vector for the pixel on basis of a motionmodel being determined on basis of a part of (402-436) a motion vectorfield (400) of the image; comparing the model-based motion vector witheach of the motion vectors of the set of motion vectors; and selecting aparticular motion vector of the set of motion vectors on basis of thecomparing and for assigning the particular motion vector as thebackground motion vector.